jackaduma / cyclegan-vc2 Goto Github PK

librosa.output was removed in librosa version 0.8.0. Soundfile could be used instead. Thanks.

Dear friend,

PS D:\CycleGAN-VC2-master\CycleGAN-VC2-master> python train.py
Traceback (most recent call last):
File "train.py", line 520, in
cycleGAN = CycleGANTraining(logf0s_normalization=logf0s_normalization,
File "train.py", line 106, in init
self.start_epoch = self.loadModel(restart_training_at)
File "train.py", line 442, in loadModel
checkPoint = torch.load(PATH)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 595, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 774, in _legacy_load
result = unpickler.load()
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 730, in persistent_load
deserialized_objects[root_key] = restore_location(obj, location)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 175, in default_restore_location
result = fn(storage, location)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 151, in _cuda_deserialize
device = validate_cuda_device(location)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\serialization.py", line 135, in validate_cuda_device
raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.

but when i input the torch.cuda.is_available() under python cmd, the return value is true.
this issue block me for days,any suggestion will work?

cannot thank more.

训练之后是否可以将文本转为某个人音色的语音？

Hello, I just started to learn voice conversion.And I want to know how to write a demo by using this frame? How do I use another person’s voice to speak the content of the person’s speech with the voice in the training set?

Is it necessary to have a pre-trained model to start training? Can we train directly without a pretrained model?

I am checking the model provided in this repository. How to do the inference of the given model? I want to check the model using my dataset. How to generate the output by passing our wavfile?

FileNotFoundError: [Errno 2] No such file or directory: './model_checkpoint/_CycleGAN_CheckPoint'
请问换其他数据集测试的时候，报上述错误是怎么回事呀，求解答

I want to know the final loss of D and G

Is there any way to re-synthesis new audio using the trained model? I don't know whether I miss some info or the info such as synthesis.py is left out.
Thanks in advance.

在自己的服务器上使用预训练模型跑了一周左右，但是得到的转换效果仍然不理想，得出的结果就像是A的语速和韵律变成了B的语速和韵律，但是总体听上去说话人的身份好像并没改变，只是语速和韵律和目标说话人的一样

请问这个模型跑多长时间才能得到比较好的效果，在训练过程中有没有什么技巧，能够让转换之后的声音效果更好

谢谢您

Hey, am I missing something or the second step adverserial loss is missing in this implementation?

请问这个_CycleGAN_CheckPoint是怎么才能有啊

1. 如果我有A数据量很多，B数据量较少，通过B转换为A的音色，效果会怎样呢？

2. 关于数据量的关系，您有相关的分析吗？例如ABCD数据量都较多，是否相互转换音质高一点呢？又例如A多B少，A转B和B转A效果各自会怎样？

3. 男声和女声之间的转换效果如何？

4. 怎样的声音转换的效果会好一点？

5. 这个方案做多个说话人转为一个说话人有效果吗？

6. 另外，Donation可以提供支付宝或微信二维码，**同学更熟悉。

https://arxiv.org/abs/2010.11672
Accepted to Interspeech 2020.

File "train.py", line 521, in
cycleGAN.train()
File "train.py", line 147, in train
for i, (real_A, real_B) in enumerate(train_loader):
File "C:\Users\mike\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\utils\data\dataloader.py", line 363, in next
data = self._next_data()
File "C:\Users\mike\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\utils\data\dataloader.py", line 403, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "C:\Users\mike\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\utils\data_utils\fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "C:\Users\mike\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\torch\utils\data_utils\fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "C:\Users\mike\Desktop\cycleganvc\trainingDataset.py", line 47, in getitem
assert frames_B_total >= n_frames
AssertionError

when trying to use my own training data
After I pre process my data and run the training I get this

however if I pre process the data you supplied and use that cache file it works

Any suggestions?
16khz mono 32 bit floats

你好！我最近在尝试复现ASSERT论文，但是在数据集预处理方面遇到了一些问题，我有看到你在issue中回答，可以咨询一下相关问题嘛？
非常期待您的解答，万分感谢！！